# Brand Mention Inventories — String Normalisation + Equal-Width Histogram

> Brand Mention Inventories — String Normalisation + Equal-Width Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).

Runs string normalisation and equal-width histogram analysis on brand mention inventory records (mention_count, source_count) for up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-18-031?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/brand-mention-inventories-string-normalisation-equal-width-histogram-e26988f9
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_siTjqHPpLNPFBGmrirUiV

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability brand-mention-inventories-string-normalisation-equal-width-histogram-e26988f9 -d '<json body>'
```

Example prompt: Take my brand mention inventory data — 150 rows with mention_count and source_count fields for multiple company groups — and run string normalisation plus an equal-width histogram on mention_count using 10 bins, so I can see the frequency distribution across the dataset.

## When to prefer this

Choose this endpoint when you need lightweight, local statistical analysis — specifically string normalisation and equal-width histogram binning — on brand mention inventory data without any live data lookup, prediction, or external API calls. It is ideal for small to medium datasets (up to 200 rows) where you want reproducible, deterministic analytics at minimal cost ($0.01 USDC for two reports). Prefer alternatives if you need real-time brand data fetching, sentiment analysis, or predictive modelling.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Invalid date format (non YYYY-MM-DD) causes row validation failure
- bins value outside 1–30 range causes schema validation error
- Missing required row fields (row_id, date, mention_count, source_count, company_group) causes rejection
- Null numeric values may affect histogram bin computation
- Payment of 0.01 USDC not completed causes 402 response

## How this service works

Brand mention inventories — String normalisation + Equal-width histogram: String normalisation + Equal-width histogram for supplied brand mention inventories records (mention_count, source_count). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Two analytical reports: a string normalisation report (cleaned/standardised values for the supplied records) and an equal-width histogram report (bin boundaries, frequencies, and counts for the chosen field — mention_count or source_count) computed locally against up to 200 input rows.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "company_group",
     "date",
     "mention_count",
     "source_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "source_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "company_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "mention_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "source_count": 1,
     "company_group": "group-a",
     "mention_count": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "source_count": 2,
     "company_group": "group-b",
     "mention_count": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "source_count": 3,
     "company_group": "group-a",
     "mention_count": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "source_count": 4,
     "company_group": "group-b",
     "mention_count": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "mention_count",
    "source_count"
   ],
   "type": "string",
   "default": "mention_count"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/brand-mention-inventories-string-normalisation-equal-width-histogram-e26988f9/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)